AI Model Reinforcement Graduate (Platform Responsibility) - 2027 Start

Responsibilities

About the Team
Generative AI and large language models are reshaping the core capabilities of global content platforms - and high-quality training and evaluation data is one of the key factors that determines a model's ceiling.

The Safety Model Operations [SMO] team is responsible for building, optimizing, and maintaining machine learning models and operational processes that support TikTok's Trust & Safety systems. We ensure that automated safety models perform effectively in identifying harmful content, mitigating risks, and maintaining a safe user environment across regions.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities
- For large-model training and evaluation scenarios, participate in formulating and continuously iterating data quality standards, judgment rules, and acceptance criteria.
- Review and assess data outputs against quality standards, identify issues, and close the loop on corrections to ensure accuracy and consistency.
- Participate deeply in the assessment and discussion of complex, ambiguous, and edge cases, turning findings into reusable judgment rules and knowledge assets.
- Track quality performance, identify root causes, and drive improvements in production processes and execution.
- Collaborate with production, product, algorithm, strategy, and other teams to align quality standards and connect the "standards-production-acceptance-feedback" loop.

Qualifications

Minimum Qualification(s)
- Bachelor's degree
- Excellent English listening, speaking, reading, and writing skills, including accurate comprehension of English video and text. IELTS 7.5, TOEFL 105, or equivalent.
- Familiarity with Excel and other common data-processing tools.
- Clear logic and strong structured decomposition, abstraction, synthesis, judgment, and communication skills. Detail-oriented, with an independent view of what constitutes high-quality data.

Preferred Qualification(s)
- Majors in law, philosophy, economics, journalism, languages, social sciences, or related fields are preferred.
- Internship or project experience in data quality, content moderation, compliance, content operations, AI data, or annotation is preferred.
- Deep experience with mainstream foundation-model products such as ChatGPT, Claude, Gemini and a basic understanding of AI capability boundaries, are preferred.

Responsibilities

Responsibilities

About the Team
Generative AI and large language models are reshaping the core capabilities of global content platforms - and high-quality training and evaluation data is one of the key factors that determines a model's ceiling.

The Safety Model Operations [SMO] team is responsible for building, optimizing, and maintaining machine learning models and operational processes that support TikTok's Trust & Safety systems. We ensure that automated safety models perform effectively in identifying harmful content, mitigating risks, and maintaining a safe user environment across regions.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities
- For large-model training and evaluation scenarios, participate in formulating and continuously iterating data quality standards, judgment rules, and acceptance criteria.
- Review and assess data outputs against quality standards, identify issues, and close the loop on corrections to ensure accuracy and consistency.
- Participate deeply in the assessment and discussion of complex, ambiguous, and edge cases, turning findings into reusable judgment rules and knowledge assets.
- Track quality performance, identify root causes, and drive improvements in production processes and execution.
- Collaborate with production, product, algorithm, strategy, and other teams to align quality standards and connect the "standards-production-acceptance-feedback" loop.

Qualifications

Qualifications

Minimum Qualification(s)
- Bachelor's degree
- Excellent English listening, speaking, reading, and writing skills, including accurate comprehension of English video and text. IELTS 7.5, TOEFL 105, or equivalent.
- Familiarity with Excel and other common data-processing tools.
- Clear logic and strong structured decomposition, abstraction, synthesis, judgment, and communication skills. Detail-oriented, with an independent view of what constitutes high-quality data.

Preferred Qualification(s)
- Majors in law, philosophy, economics, journalism, languages, social sciences, or related fields are preferred.
- Internship or project experience in data quality, content moderation, compliance, content operations, AI data, or annotation is preferred.
- Deep experience with mainstream foundation-model products such as ChatGPT, Claude, Gemini and a basic understanding of AI capability boundaries, are preferred.